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BMCBI
2005

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

8 years 12 months ago
GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA
Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence- and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN (available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component al...
Robert G. Beiko, Robert L. Charlebois
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where BMCBI
Authors Robert G. Beiko, Robert L. Charlebois
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